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Probabilistic information on object weight shapes force dynamics in a grip-lift task

机译:有关物体重量形状的概率信息会在抓地力提升任务中推动动力学

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Advance information, such as object weight, size and texture, modifies predictive scaling of grip forces in a grip-lift task. Here, we examined the influence of probabilistic advance information about object weight. Fifteen healthy volunteers repeatedly grasped and lifted an object equipped with a force transducer between their thumb and index finger. Three clearly distinguishable object weights were used. Prior to each lift, the probabilities for the three object weights were given by a visual cue. We examined the effect of probabilistic pre-cues on grip and lift force dynamics. We expected predictive scaling of grip force parameters to follow predicted values calculated according to probabilistic contingencies of the cues. We observed that probabilistic cues systematically influenced peak grip and load force rates, as an index of predictive motor scaling. However, the effects of probabilistic cues on force rates were nonlinear, and anticipatory adaptations of the motor output generally seemed to overestimate high probabilities and underestimate low probabilities. These findings support the suggestion that anticipatory adaptations and force scaling of the motor system can integrate probabilistic information. However, probabilistic information seems to influence motor programs in a nonlinear fashion.
机译:预先的信息(例如物体的重量,大小和纹理)会修改抓地力任务中抓地力的预测比例。在这里,我们研究了关于物体重量的概率提前信息的影响。 15名健康志愿者反复抓住并提起一个在拇指和食指之间装有力传感器的物体。使用了三个明显可区分的物体重量。在每次举升之前,通过视觉提示给出三个物体权重的概率。我们研究了概率预兆对抓地力和提升力动力学的影响。我们期望抓地力参数的预测缩放能够遵循根据提示的概率偶然性计算出的预测值。我们观察到,概率线索系统地影响了峰值抓地力和负载力率,这是预测性电动机缩放的指标。然而,概率提示对力率的影响是非线性的,并且对电动机输出的预期适应通常似乎高估了高概率,而低估了低概率。这些发现支持了这样的建议,即电动机系统的预期适应和力缩放可以整合概率信息。但是,概率信息似乎以非线性方式影响运动程序。

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